Technical Field
The present disclosure relates to readers to read machine-readable symbols.
Description of the Related Art
Machine-readable symbols encode information in a form that can be optically read via an appropriately configured machine-readable symbol reader or scanner. Machine-readable symbols take a variety of forms, the most commonly recognized form being the linear or one-dimensional barcode symbol. Other forms include two-dimensional machine-readable symbols such as stacked code symbols, and area or matrix code symbols. These machine-readable symbols are typically composed of patterns of high and low reflectance areas. For instance, a barcode symbol may comprise a pattern of black bars on a white background. Also for instance, a two-dimensional symbol may comprise a pattern of black marks (e.g., bars, squares or hexagons) on a white background. Machine-readable symbols are not limited to being black and white, but may comprise two other colors, may include more than two colors (e.g., more than black and white), may comprise directly marked materials having the symbols formed in surface relief, and/or may comprise electronic media displayed by an illuminated screen or display of an electronic device such as a cell phone.
Machine-readable symbols are typically composed of elements (e.g., symbol characters) which are selected from a particular machine-readable symbology. Information is encoded in the particular sequence of shapes (e.g., bars) and spaces which may have varying dimensions. The machine-readable symbology provides a mapping between machine-readable symbols or symbol characters and human-readable symbols (e.g., alpha, numeric, punctuation, commands). A large number of symbologies have been developed and are in use, for example Universal Product Code (UPC), European Article Number (EAN), Code 39, Code 128, Data Matrix, PDF417, etc.
Machine-readable symbols have widespread and varied applications. For example, machine-readable symbols can be used to identify a class of objects (e.g., merchandise) or unique items (e.g., patents). As a result, machine-readable symbols are found on a wide variety of objects, such as retail goods, company assets, and documents, and help track production at manufacturing facilities and inventory at stores (e.g., by scanning items as they arrive and as they are sold). In addition, machine-readable symbols may appear on a display of a portable electronic device, such as a mobile telephone, personal digital assistant, tablet computer, laptop computer, or other device having an electronic display. For example, a customer, such as a shopper, airline passenger, or person attending a sporting event or theater event, may cause a machine-readable symbol to be displayed on their portable electronic device so that an employee (e.g., merchant-employee) can read the machine-readable symbol via a data reader to allow the customer to redeem a coupon or to verify that the customer has purchased a ticket for the event.
Machine-readable symbol readers or data readers are used to capture images or representations of machine-readable symbols appearing on various surfaces to read the information encoded in the machine-readable symbol. One commonly used machine-readable symbol reader is an imager- or imaging-based machine-readable symbol reader. Imaging-based machine-readable symbol readers typically employ flood illumination to simultaneously illuminate the entire machine-readable symbol, either from dedicated light sources, or in some instances using ambient light. Such is in contrast to scanning or laser-based (i.e., flying spot) type machine-readable symbol readers, which scan a relatively narrow beam or spot of light sequentially across the machine-readable symbol.
Imaging-based machine-readable symbol readers typically include solid-state image circuitry, such as charge-coupled devices (CCDs) or complementary metal-oxide semiconductor (CMOS) devices, and may be implemented using a one-dimensional or two-dimensional imaging array of photosensors (or pixels) to capture an image of the machine-readable symbol. One-dimensional CCD or CMOS readers capture a linear cross-section of the machine-readable symbol, producing an analog waveform whose amplitude represents the relative darkness and lightness of the machine-readable symbol. Two-dimensional CCD or CMOS readers may capture an entire two-dimensional image. The image is then processed to find and decode a machine-readable symbol. For example, virtual scan line techniques for digitally processing an image containing a machine-readable symbol sample across an image along a plurality of lines, typically spaced apart and at various angles, somewhat like a scan pattern of a laser beam in a scanning or laser-based scanner.
Reading a symbol typically employs generating an electrical signal having an amplitude determined by the intensity of the collected light. Relatively less reflective or darker regions (e.g., bars or other marks) may, for example, be characterized or represented in the electrical signal by an amplitude below a threshold amplitude, while relatively more reflective or lighter regions (e.g., white spaces) may be characterized or represented in the electrical signal by an amplitude above the threshold amplitude. When the machine-readable symbol is imaged, positive-going and negative-going transitions in the electrical signal occur, signifying transitions between darker regions and lighter regions. Techniques may be used for detecting edges of darker regions and lighter regions by detecting the transitions of the electrical signal. Techniques may also be used to determine the dimensions (e.g., width) of darker regions and lighter regions based on the relative location of the detected edges and decoding the information represented by the machine-readable symbol.
In machine-readable symbol readers, a return light signal from the object or symbol being read is focused onto a sensor or sensor array. In the example of a machine-readable symbol reader reading marks and spaces of a typical machine-readable symbol, there needs to be sufficient difference in signal intensity between the signal corresponding to the light space and the signal corresponding to the dark bar in order for the processor to differentiate therebetween. Given the variety of types of machine-readable symbols in use and the variety of types of media or materials on which they can be used or displayed, it can be difficult to create a single set of conditions (such as through illumination, aperture, acquisition speed or shutter speed) suitable for general use. For example, in some instances a machine-readable symbol reader reads machine-readable symbols printed on a piece of media, e.g., paper, card board, metal. The media can have various surface characteristics from generally specularly diffusive (e.g., untreated or uncoated paper or cardboard) to generally specularly reflective (e.g., aluminum cans, reflective packaging such a metallic Mylar packaging, coated paper or coated cardboard). In other instances, a machine-readable symbol reader reads machine-readable symbols printed on a display screen of an electronic device (e.g., tablet computer, smartphone, smartwatch, personal digital assistant, electronic reader or book).